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Data Engineering Leader

hace 2 semanas

Buenos Aires, Buenos Aires C.F., Argentina Kimberly-Clark A tiempo completo

About Us

Kimberly-Clark is a leading consumer goods company that creates iconic brands like Huggies, Kleenex, and Cottonelle. We're committed to driving innovation, growth, and impact through our talented professionals.

Our Mission

We strive to create Better Care for a Better World by delivering high-quality products and services that meet the needs of our consumers. Our team is dedicated to making a difference through sustainable practices, inclusion, wellbeing, and career development.

Your Role

You'll be part of our multidisciplinary agile team, working closely with data scientists, analysts, and other team members to design and implement scalable enterprise data solutions on Cloud Platforms. Your expertise in architecting solutions within the Snowflake ecosystem will help us deliver better care for billions of people around the world.

Main Responsibilities:

  1. Design and operationalize enterprise data solutions on Cloud Platforms: Develop and implement scalable and secure data solutions on cloud platforms, ensuring they meet enterprise standards and requirements.
  2. Integrate Azure services, Snowflake technology, and other third-party data technologies: Seamlessly integrate various data technologies, including Azure services, Snowflake, and other third-party tools, to create a cohesive data ecosystem.
  3. Build and maintain high-quality data pipelines for analytic solutions: Develop robust data pipelines that automate the extraction, transformation, and loading (ETL) of data from various sources into a centralized data warehouse or lake.
  4. Collaborate with a multidisciplinary agile team to generate insights from connected data.
  5. Manage and create data inventories for analytics and APIs to be consumed: Develop and maintain comprehensive data inventories that catalog available data assets and their metadata.
  6. Design data integrations with internal and external products: Architect and implement data integration solutions that enable seamless data exchange between internal systems and external partners or products.
  7. Build data visualizations to support analytic insights: Create intuitive and insightful data visualizations using tools like PowerBI to help stakeholders understand complex data sets and derive actionable insights.

Key Qualifications and Experiences:

  • 5+ years of experience tailoring, configuring, and crafting solutions within the Snowflake environment.
  • 3+ years demonstrated expertise in architecting solutions within the Snowflake ecosystem.
  • 10+ years of data engineering or design experience, designing, developing, and deploying scalable enterprise data analytics solutions.
  • Expertise in data modeling principles/methods, including conceptual, logical & physical data models for data warehouses, data lakes, and/or database management systems.
  • 5+ years of hands-on experience designing, building, and operationalizing data solutions and applications using cloud data and analytics services.
  • 10+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
  • 10+ years of experience with database development and scripting.
  • Deep understanding of data architecture, data engineering, data warehousing, data analysis, reporting, and data science techniques and workflows.
  • Skilled in creating data products that support analytic solutions.
  • Proficiency in working with APIs and understanding data structures to serve them.
  • Experience with Object-Relational Mapping (ORM) frameworks.
  • Knowledge of managing sensitive data, ensuring data privacy and security.
  • Expertise in data visualization tools, specifically PowerBI.
  • Strong problem-solving skills and ability to work as part of a technical, cross-functional analytics team.
  • Experience with relational and non-relational databases (NoSQL, graph databases, etc.).
  • Agile learner with a passion for solving complex data problems and delivering insights.
  • Proficiency in programming languages such as SQL, NoSQL, Python, Java, R, and Scala.
  • Familiarity with relational and non-relational databases, including GraphQL and MongoDB.
  • Experience with ETL (extract, transform, and load) systems and API integrations.
  • Understanding of data storage solutions, knowing when to use a data lake versus a data warehouse.
  • Ability to write scripts for automation and repetitive task management.
  • Bachelor's degree in management information systems/technology, Computer Science, Engineering, or related discipline.
  • Minimum 10+ years of experience in designing large-scale data solutions, performing design assessments, crafting design options and analysis, finalizing preferred solution choice working with IT and Business stakeholders.